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This repository was archived by the owner on May 28, 2019. It is now read-only.
Creating norm_info_mgc_lf0_vuv_bap_63_MVN.dat for the Full VCTK dataset #49
For large datasets, where extract_feats.py uses it's multifolder feature like the full VCTK dataset; it's unclear what the norm_info/norm.dat file is. The norm_info_mgc_lf0_vuv_bap_63_MVN.dat file is regenerated for each tmp split of the dataset. How do you create the norm_info/norm.dat for datasets with more than 5000 files?
I believe you had to deal with the same problem with the 22 speaker dataset because it contains around 8000 files.
Thanks for your time, Michael. Happy to contribute back the findings.
changed the title [-]Creating norm_info_mgc_lf0_vuv_bap_63_MVN.dat [/-][+]Creating norm_info_mgc_lf0_vuv_bap_63_MVN.dat for the Full VCTK dataset[/+]on Mar 29, 2018
@macarbonneau Have you run this? Is it OKAY to just recompute the mean and the STD?
It looks like the data is recreated in the generation code using the mean and the STD; therefore, every numpy features (.npz) file needs to be updated to fit the new mean and the new STD. I want to make sure i'm understanding this correctly.
Why not just put all your .wav files in the same folder and extract npz feature on this folder. Anyway, you will have to combine them in a numpy_features/ and a numpy_features_valid/ folder later. Voiceloop uses the prefix in your file name to determine speaker ID.
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[-]Creating norm_info_mgc_lf0_vuv_bap_63_MVN.dat [/-][+]Creating norm_info_mgc_lf0_vuv_bap_63_MVN.dat for the Full VCTK dataset[/+]niravpatel2008 commentedon Mar 29, 2018
@PetrochukM i also have large dataset for single speaker. it around 13k files. can you please share you changes so i can apply to my side.
macarbonneau commentedon Mar 29, 2018
This post will answer your question: #11
PetrochukM commentedon Mar 29, 2018
@macarbonneau Have you run this? Is it OKAY to just recompute the mean and the STD?
It looks like the data is recreated in the generation code using the mean and the STD; therefore, every numpy features (.npz) file needs to be updated to fit the new mean and the new STD. I want to make sure i'm understanding this correctly.
macarbonneau commentedon Mar 29, 2018
This sounds very complicated.
Why not just put all your .wav files in the same folder and extract npz feature on this folder. Anyway, you will have to combine them in a numpy_features/ and a numpy_features_valid/ folder later. Voiceloop uses the prefix in your file name to determine speaker ID.
This is what I did and it works fine.
PetrochukM commentedon Mar 29, 2018
They are in the same folder.
When I run
extract_featswith 40,000 files, it splits them up because its over a 5,000 file limit here:https://gist.github.com/kastnerkyle/cc0ac48d34860c5bb3f9112f4d9a0300#file-extract_feats-py-L1339
Did you disable this feature?
macarbonneau commentedon Mar 29, 2018
Oh yeah... I played a bit with the script. I don't think this part is active anymore in my code.
PetrochukM commentedon Mar 29, 2018
@macarbonneau O nice. Can you post a gist?